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remain limited due to a lack of systematic comparisons and underused legacy datasets. This project will develop a framework to predict sediment properties directly from geophysical data. Legacy SI data
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remain limited due to a lack of systematic comparisons and underused legacy datasets. This project will develop a framework to predict sediment properties directly from geophysical data. Legacy SI data
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. Overview This PhD project is part of the EPSRC Centre for Doctoral Training in Process Industries: Net Zero (PINZ) . The PINZ CDT will train the next generation of process and chemical engineers, and
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to work at the NQCC to apply their research within the national labs framework. This position is part of an annual NQCC cohort of 6 collaborative studentships, in which the projects have been co-developed
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seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of social and networking
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medicine, reducing reliance on animal models and advancing mechanobiology-informed materials design. We seek a motivated, creative, and curious PhD candidate excited to bridge disciplines and co-develop
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on empirical optimisation, leading to inefficiencies in energy use and impurity removal. This PhD project proposes to develop a Coupled Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) model
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) into the tumour pre-operatively. Wireless methods hold promise however, due to the scale of current RFID tags, delivery is problematic for both clinicians and patients. The PhD provides an opportunity to develop
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The Open University Business and Law Schools are inviting applications to join our campus-based PhD Programme and our new PhD by Distance Learning Programme. The starting date for both programmes is
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development, collaborate with experts across disciplines, and contribute to open-source tools that advance the wider AI community, and support long-term societal impact. We welcome applicants from background